Computational Analysis Problem of Aesthetic Content in Fine-Art Paintings

Author:

Zhuravleva Olga A.1ORCID,Savkhalova Natalie B.2ORCID,Komarov Andrei V.1ORCID,Zherdev Denis A.3ORCID,Demina Anna I.1ORCID,Michaelsen Eckart4ORCID,Nikonorov Artem V.1ORCID,Nesterov Alexander Yu.1ORCID

Affiliation:

1. Samara National Research University

2. “Center of Spiritual Culture” International Public Organization

3. Samara National Research University; Image Processing Systems Institute, Russian Academy of Sciences

4. Fraunhofer Institute of Optronics, System Technologies and Image Exploitation

Abstract

The article discusses the possibilities of the formal analysis of the fine-art painting composition on the basis of the classical definitions of beauty and computational aesthetics’ approaches of the second half of the 20th century he authors define the problem and consider solutions for the formalization of aesthetic perception in the context of aesthetic text, i.e., as part of the fine arts composition – a formal sequence of signs simply ordered in accordance with the syntactic rules’ system. The methodology of the research is defined by the general semiotics, distinguishing semantics, syntax, and pragmatics of a sign, by the aesthetic analysis’ methods, ranging according to the author’s message aesthetics, receptive aesthetics, and text aesthetics, as well as by the computational analysis methods connected with neural network means of defining the images’ symmetry. The article reveals preconditions for the emergence and also the current state of computational aesthetics as an interdisciplinary branch of knowledge. Analyzing the problem from the perspective of philosophy, aesthetics, semiotics, and technology, the authors draw attention to the need to improve the computational aesthetics methods. Firstly, the existing methods do not always enable to describe the fine-art object adequately. Secondly, there exists the so-called reduction of aesthetic assertion transforming it into the assertion concerning the object’s external characteristics. As a result, the authors assume that the increasing complexity of the current mathematical models and the experts’ subjective assessment support will allow to reach a compromise solution that enables the development of computational aesthetics as a branch of knowledge. Enhancement and development of the mathematical models, taking into account the rules of semiotics and subjectivism of the human perception, is the relevant objective of computational analysis of the aesthetic fine-arts text. The results of the present research supports the classic statement regarding the underivability of semantic and pragmatic propositions from syntax. The research concludes that relevant objectives are to find a correlation between, one the one hand, the axes and points of symmetry, deriving from the neural simulation, and, on the other hand, aesthetic effect, emerging from the perception of fine-art paintings.

Publisher

Humanist Publishing House

Subject

General Medicine

Reference27 articles.

1. Alberti L.B. (1935) The Ten Books of Architecture: in 2 Vols (Vol. 1). Moscow: All-Union Architecture Academy Press (in Russian).

2. Bense M. (1968) Einfuhrung in die Informationsasthetik. In: Ronge H. (Ed.) Kunst und Kybernetik (pp. 28–41). Köln: DuMont (in German).

3. Birkhoff G.D. (1933) Aesthetic Measure. Cambridge: Harvard University Press.

4. Brachmann A. & Redies C. (2017) Computational and Experimental Approaches to Visual Aesthetics. Frontiers in Computational Neuroscience. Vol. 11, art. 102.

5. Cetinic E., Lipic T., & Grgic S. (2019) A Deep Learning Perspective on Beauty, Sentiment, and Remembrance of Art. IEEE Access. Vol. 7, pp. 73694–73710.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3